Table of Contents 
Cover 
Title Page 
Copyright 
Dedication 
About the Authors 
Credits 
Acknowledgments 
Introduction 
The Origins of Kettle 
About This Book 
How This Book Is Organized 
Prerequisites 
On the Website 
Further Resources 
Part I: Getting Started 
Chapter 1: ETL Primer 
OLTP versus Data Warehousing 
What Is ETL? 
ETL, ELT, and EII 
Data Integration Challenges 
ETL Tool Requirements 
Summary 
Chapter 2: Kettle Concepts 
Design Principles 
The Building Blocks of Kettle Design 
Parameters and Variables 

Visual Programming 
Summary 
Chapter 3: Installation and Configuration 
Kettle Software Overview 
Installation 
Configuration 
Summary 
Chapter 4: An Example ETL Solution—Sakila 
Sakila 
Prerequisites and Some Basic Spoon Skills 
The Sample ETL Solution 
Summary 
Part II: ETL 
Chapter 5: ETL Subsystems 
Introduction to the 34 Subsystems 
Summary 
Chapter 6: Data Extraction 
Kettle Data Extraction Overview 
Working with ERP and CRM Systems 
Data Profiling 
CDC: Change Data Capture 
Delivering Data 
Summary 
Chapter 7: Cleansing and Conforming 
Data Cleansing 
Error Handling 
Auditing Data and Process Quality 
Deduplicating Data 
Scripting 
Summary 
Chapter 8: Handling Dimension Tables 
Managing Keys 
Loading Dimension Tables 
Slowly Changing Dimensions 

More Dimensions 
Summary 
Chapter 9: Loading Fact Tables 
Loading in Bulk 
Dimension Lookups 
Fact Table Handling 
Summary 
Chapter 10: Working with OLAP Data 
OLAP Benefits and Challenges 
Working with Mondrian 
Working with XML/A Servers 
Working with Palo 
Summary 
Part III: Management and Deployment 
Chapter 11: ETL Development Lifecycle 
Solution Design 
Agile Development 
Testing and Debugging 
Documenting the Solution 
Summary 
Chapter 12: Scheduling and Monitoring 
Scheduling 
Monitoring 
Summary 
Chapter 13: Versioning and Migration 
Version Control Systems 
Kettle Metadata 
Managing Repositories 
Version Migration System 
Summary 
Chapter 14: Lineage and Auditing 
Batch-Level Lineage Extraction 
Lineage 
Logging and Operational Metadata 

Summary 
Part IV: Performance and Scalability 
Chapter 15: Performance Tuning 
Transformation Performance: Finding the Weakest Link 
Improving Transformation Performance 
Improving Job Performance 
Summary 
Chapter 16: Parallelization, Clustering, and Partitioning 
Multi-Threading 
Using Carte as a Slave Server 
Clustering Transformations 
Partitioning 
Summary 
Chapter 17: Dynamic Clustering in the Cloud 
Dynamic Clustering 
Cloud Computing 
EC2 
Summary 
Chapter 18: Real-Time Data Integration 
Introduction to Real-Time ETL 
Transformation Streaming 
Summary 
Part V: Advanced Topics 
Chapter 19: Data Vault Management 
Introduction to Data Vault Modeling 
Do You Need a Data Vault? 
Data Vault Building Blocks 
Transforming Sakila to the Data Vault Model 
Loading the Data Vault: A Sample ETL Solution 
Updating a Data Mart from a Data Vault 
Summary 
Chapter 20: Handling Complex Data Formats 